Motion artifact reduction using multi-channel PPG signals

ABSTRACT

A data processing device is disclosed for extracting a desired vital signal containing a physiological information component from sensor data that includes time-dependent first sensor data comprising the physiological information component and at least one motion artifact component, and that includes time-dependent second sensor data that is indicative of a position, a velocity or an acceleration of the sensed region as a function of time. A decomposition unit decomposes the second sensor data into at least two components of decomposed sensor data and, based on the decomposed second sensor data, provides at least two different sets of motion reference data in at least two different motion reference data channels. An artifact removal unit determines the vital signal formed from a linear combination of the first sensor data and the motion reference data of at least one two of the motion reference data channels.

CROSS REFERENCE TO RELATED APPLICATIONS

The present application is a continuation of International ApplicationNo. PCT/EP2015/060864, filed on May 18, 2015, which claims the benefitof European Application No. 14170178.9, filed May 28, 2014. Theseapplications are hereby incorporated by reference herein for allpurpose.

TECHNICAL FIELD

The present embodiment relates to data processing device for extractinga desired vital signal, which contains a physiological informationcomponent pertaining to a subject of interest, from photoplethysmographydata. It also relates to a photoplethysmography device, to a dataprocessing method for extracting a desired vital signal, which containsa physiological information component pertaining to a subject ofinterest, from photoplethysmography data, and to a computer program.

BACKGROUND

Information about cardiovascular status, such as blood oxygensaturation, heart and respiratory rates can be unobtrusively acquired byphotoplethysmography (PPG) using sensors such as contact sensors orremote sensors such as a camera. A PPG technique using a remote sensoris also referred to as remote PPG.

Whether using contact sensors or remote sensors, the PPG technique issusceptible to motion-induced signal distortions, which are superimposedto the desired vital signal. Distortions of the signals ascertained byPPG also arise from motion of the subject. Motion artifact reduction inPPG data representing the detected PPG signals is a challenging tasksince the contribution of the motion components often exceeds thecontribution of the desired vital signal by an order of magnitude. Theartifacts lead to erroneous interpretation and degrade the accuracy andreliability of estimation of cardiovascular parameters.

In a number of studies the associated PPG setups were usually operatedunder conditions that required the subjects to be motionless. Thisdrawback limits the capabilities of the technique in real applicationenvironments, e.g., hospital and sports.

US 2013/0070792 A1 discloses techniques for denoising of physiologicalsignals. A signal (e.g., physiological signal) comprising at least twosignal channels is decomposed using independent component analysis (ICA)into at least two independent components. Then, independent component(IC) denoising is applied to estimate which of the at least twoindependent components belongs to a signal space and which of the atleast two independent components belongs to a noise space using astatistical metric associated with the at least two signal channels. Ade-noised version of the signal is generated by preserving in the signalonly one or more independent components of the at least two independentcomponents belonging to the signal space.

WO 2014/020463 A1 describes a device and a method for extractingphysiological information from electromagnetic radiation emitted orreflected by a subject. A data stream derived from detectedelectromagnetic radiation is received. The data stream comprises a firstsequence of signal samples indicative of various spectral portions. Thedata stream is split into at least two deduced staggered sequences ofregistered signal samples. Each of the deduced staggered sequencesrepresents a defined spectral portion and comprises indicative signalsamples spaced in time. Artificial samples are generated underconsideration of proximate indicative signal samples so as to at leastpartially replace blank spaces between the indicative signal samples.This way, a supplemented data stream is generated.

WO 2013/038326 A1 is related to a device and a method for extractinginformation from remotely detected characteristic signals. A data streamderivable from electromagnetic radiation emitted or reflected by anobject is received. The data stream comprises a continuous or discretecharacteristic signal including physiological information and adisturbing signal portion. The physiological information isrepresentative of at least one at least partially periodic vital signal.The disturbing signal portion is representative of at least one of anobject motion portion and/or a non-indicative reflection portion. Arelevant frequency band of the data stream is split into at least twodefined sub-bands, comprising determined portions of the characteristicsignal, each of which represents a defined temporal frequency portionpotentially being of interest. The sub-bands are optimized so as toderive optimized sub-bands, the optimized sub-bands being at leastpartially indicative of a presence of the vital signal. The at least twooptimized sub-bands are combined so as to compose an optimized processedsignal.

WO 99/32030 is concerned with artifact reduction in PPG by removingmotion artifacts prior to digital processing. A method is disclosed,comprising the steps of emitting electromagnetic radiation at tissue atat least first and second different wavelengths, receiving the radiationat the different wavelengths after it has been transmitted through orreflected within the tissue, providing at least first and second signalswhich are a logarithmic measure of the received first and secondradiation wavelengths and subtracting the second signal from the firstsignal, removing a DC component of the result of the subtraction andproviding an AC component to digital sampling means, and processing thedigital samples in order to provide a desired value representing aproperty of the tissue.

US 2002/0077536 A1 describes a method and apparatus for analyzing twomeasured signals that are modeled as containing primary and secondaryportions. Coefficients relate the two signals according to a model. Inone embodiment the method involves utilizing a transformation whichevaluates a plurality of possible signal coefficients in order to findappropriate coefficients. Alternatively, the method involves usingstatistical functions or Fourier transform and windowing techniques todetermine the coefficients relating to the two measured signals. Themethods are used in blood oximetry measurements.

SUMMARY

It is an object of the present embodiment to provide a data processingdevice that achieves an improved motion artifact reduction of PPG data.

It is another object of the present embodiment to provide a PPGapparatus that achieves an improved motion artifact reduction ofascertained PPG data.

It is another object of the present embodiment to provide a dataprocessing method that achieves an improved motion artifact reduction ofPPG data.

It is a further object of the present embodiment to provide a computerprogram that achieves an improved motion artifact reduction of PPG data.

According to a first aspect of the present embodiment, a data processingdevice is provided for extracting a desired vital signal, which containsa physiological information component pertaining to a subject ofinterest, from sensor data that includes time-dependent first sensordata comprising the physiological information component and at least onemotion artifact component, and that includes time-dependent secondsensor data that is indicative of a position, a velocity or anacceleration of the sensed region as a function of time in one or morespatial dimensions. The data processing device comprises:

-   -   a decomposition unit, which is configured to receive the second        sensor data, to decompose the second sensor data into at least        two components of decomposed sensor data and to provide, based        on the decomposed second sensor data, at least two different        sets of motion reference data in at least two different motion        reference data channels,    -   an artifact removal unit, which is configured to receive the        first sensor data and the at least two different motion        reference data channels and to determine and provide at its        output the vital signal formed from a combination of the first        sensor data and the motion reference data of at least two of the        motion reference data channels.

The data processing device of the first aspect of the present embodimentis based on the recognition that a vital signal with strongly reduceddistortions due to motion artifacts can be obtained using a combinationof the first and second sensor data. Furthermore, the data processingdevice uses the additional recognition that a combination can achievethis effect particularly well based on a decomposition of the secondsensor data, which is indicative of a position, a velocity or anacceleration of the sensed region as a function of time in one or morespatial dimensions, into at least two components of decomposed sensordata.

A further advantage of the data processing device is that it does notrequire the use of previously recorded sensor data or, in other words, asensor-data history for reducing motion artifacts in the first sensordata. In this way, it is distinguished in particular from known adaptivefiltering techniques which require referring to the recent past to makeadaptations in a filtering of current sensor data. However, in thepresence of unpredictable, instant changes of the sensor data, which maybe caused by fast accelerating movements performed by the subject ofinterest (e.g., a user or a patient), such references to the sensor-datahistory lead to inferior filtering results with regard to the desiredremoval of motion artifacts. In contrast, the data processing of thepresent embodiment has an improved performance in this regard and istherefore particularly suited to be operated in combination with PPGapparatus for use in a hospital or in sports. This way, the dataprocessing device of the first aspect of the present embodiment forms akey to an increased use of PPG apparatus in medical environments as wellas every-day life.

As is known per se from PPG techniques, the sensed region is forinstance a region of skin of the subject of interest. The sensed regionmay also comprise tissue and blood vessels arranged below the skin ofthe subject of interest, in particular where transmitted electromagneticradiation is used.

In the following, embodiments of the data processing device will bedescribed.

Embodiments of the data processing device are configured to structurethe incoming time-dependent sensor data into frames containing sensordata pertaining to predetermined time spans, wherein the decompositionunit is configured to decompose the second sensor data on aframe-by-frame basis, and the artifact removal unit is configured todetermine the combination of the first sensor data and the motionreference data on the frame-by-frame basis. Frames may in differentembodiments either overlap in time or strictly partition the data indisjoint time intervals. In embodiments that are suitable in particularfor real-time processing, a frame may represent a concatenation of theincoming sensor data and a number of seconds of sensor data from therecent past.

A frame of sensor data, such as PPG data and/or accelerometer data, isthus to be understood as a data structure containing the time-dependentsensor data pertaining to a predetermined interval (a time window) of atime base. For instance, a frame may cover a number of seconds, inparticular less than 10 seconds, preferably less than 5 seconds, and forinstance at least 2 seconds. These given values are exemplary and may bevaried in dependence on a sampling rate of the sensor data.

In this embodiment in particular, no reference to a previously (i.e.,before the currently processed frame) recorded sensor data is made fordecomposing a current frame in the decomposition unit. Since thedecomposition unit processes the second sensor data, it preferably doesnot receive, or it neglects the first sensor data pertaining to a givenframe.

Preferably, in such embodiments also the artifact removal unit isconfigured to perform its operations on a frame-by-frame basis, usingthe first sensor data and the at least two different motion referencedata channels provided by the decomposition unit, which belong to agiven frame.

The data processing device of the first aspect is particularly suitedfor an implementation that performs the data processing of the incomingsensor data in real time. Embodiments of the data processing device areconfigured to perform the described data processing in real time.

The combination of the first sensor data and the motion reference dataof at least two of the motion reference data channels, which isdetermined and provided by the artifact removal unit is in oneembodiment, is in one embodiment a linear combination. Other forms ofcombinations of the first sensor data and the motion reference data ofat least two of the motion reference data channels are possible and formdifferent embodiments.

In one embodiment, the first sensor data is PPG data indicative of anamount of electromagnetic radiation reflected from or transmittedthrough the sensed region in at least one first spectral channel that issensitive to blood volume variations in the sensed region. Preferably,the at least one first spectral channel includes electromagneticradiation having a wavelength between 500 nm and 600 nm. In somevariants of this embodiment, the at least one spectral channel coverswavelengths in the spectral interval between 530 nm and 570 nm, orbetween 540 nm and 560 nm. Preferred embodiments include the wavelengthof 550 nm, which provides a particularly high sensitivity to bloodvolume variations.

The second sensor data, which as mentioned is indicative of a position,a velocity or an acceleration of the sensed region as a function of timein one or more spatial dimensions, may be received as being indicativeof one or more different quantities, depending on the technique(s) usedto record the second sensor data. Two exemplary groups of embodimentswill be described in the following

In one group of embodiments, the second sensor data is also PPG data. Inone such embodiment, the second sensor data comprises PPG dataindicative of an amount of electromagnetic radiation reflected from ortransmitted through the sensed region in at least one second spectralchannel that is less sensitive to blood volume variations in the sensedregion than the first spectral channel. The second spectral channel mayfor example contain a wavelength interval around the wavelength of 650nm (e.g. 610-700 nm), which has a relatively lower pulsatility due toblood volume variations in the skin. In other embodiments of this type,the PPG data contains second sensor data in more than one secondspectral channel, for instance in two or three spectral channels. Inaddition to the mentioned suitable spectral channel covering awavelength interval around the wavelength of 650 nm, a further spectralchannel may be comprised in the second sensor data that covers awavelength interval around a center wavelength shorter than 550 nm, suchas for instance a center wavelength of 450 nm.

In a second group of embodiments, the second sensor data comprisesaccelerometer data indicative of a change of position, a velocity or anacceleration of an accelerometer located in the sensed region of thesubject of interest.

Second sensor data that comprise different types of data, such as PPGdata in the at least one second spectral channel and accelerometer dataare used in one embodiment, which allows further increasing areliability of motion information provided by the motion reference datato be determined by the decomposition unit.

Further groups of embodiments provide different implementations of thesignal decomposition technique employed by the decomposition unit. Inthe following, four exemplary groups will be described. Again, acombination of the embodiments, i.e., of different signal decompositiontechniques is possible.

In a first such group of embodiments, the decomposition unit isconfigured to filter the second sensor data with respect to itsfrequency components or phase components, so as to provide the at leasttwo components of decomposed second sensor data in the form of at leasttwo respective frequency components or at least two respective phasecomponents of the second sensor data. In one embodiment of this firstgroup, the second sensor data are decomposed into at least two differentsets of motion reference data in at least two different motion referencedata channels in such a way that the channels correspond to differentfrequency regions to reduce motion artifacts. By this form ofdecomposition the motion reference data determined allows reducing notonly those motion artifacts that are most prominent, e.g. a strongestharmonic of the second sensor data, but is also able to reduce otherartifacts, e.g., those caused by weaker harmonics of the second sensordata. A particular implementation of a decomposition unit that has shownto work well comprises a low-pass filter which receives the secondsensor data. The low-pass filtered signal provided in one channel of themotion reference data thus covers lower frequency range of the secondsensor data. In one form of this embodiment, the decomposition unit isfurther configured to determine a second channel of motion referencedata, which covers a higher frequency range of the second sensor data,by a calculating a difference between the second sensor data and thelow-pass-filtered motion reference data pertaining to the same point inthe time base. As an application example, in physical exercises wherethere are strong periodic movements, e.g. jogging, the first and secondharmonic of the motion artifacts are prominent and in the range of theheart-rate trace. An implementation of the data processing device thatuses the described approach applied to second sensor data in the form ofaccelerometer data has shown to reduce these two harmonics effectivelyand allow recovering the heart-rate trace which can be used for areliable determination of the heart rate.

In a second such group of embodiments, which may be understood as aparticular case of the first group in that it provides a different phasecomponent, the decomposition unit comprises a Hilbert transform stagethat receives as input data either the second sensor data or one of thefrequency or phase components of the second sensor data, and isconfigured to provide at its output Hilbert transform data forming aHilbert transform of the input data. This group of embodiments is basedon the recognition that a shift in phase may occur across frequencybetween the PPG signal(s), resulting in a motion reference data whichyields a less optimal artifact reduction. To tackle this problem themotion reference signals are fed into the Hilbert transform stage togenerate additional signals that are shifted in phase by −π/2 radiansacross frequency. The Hilbert transform data and the original secondsensor data can then be provided as an input to the artifact reductionunit. This allows compensating the shift in phase across frequencybetween the PPG signal(s) and therefore obtaining an artifact reductionthat is free from such undesired phase effects.

In a third such group of embodiments, the decomposition unit comprises asingular spectrum analysis unit, which is configured to decompose thesecond sensor data as a function of time using singular spectrumanalysis (SSA) into a sum of different components that form at least twocomponents of the decomposed second sensor data. SSA decomposes thesecond sensor data into a number of motion reference data channels whichinclude oscillatory components, varying trends and noise. The sum of thecomponents represented by these channels results again in the originalsignal. Depending on eigenvalue spectra, different embodiments usedifferent numbers of reconstructed components in combination with theoriginal first and second sensor data for artifact reduction. Aparticular example from this group of embodiments will be describedfurther below with reference to the Figures.

In a fourth such group of embodiments, wherein the second sensor dataforms a sequence of samples each allocated to a respective one of asequence of time-base values, the decomposition unit is configured todecompose the second sensor data by generating a plurality oftime-shifted components from the second sensor data, each time-shiftedcomponent being determined from the second sensor data by shifting theallocation to the time-base values by a respective predetermined numberof samples. For example, a decomposition of eight signals is realized byshifting PPG data forming the second sensor data by −4, −3, −2, −1, 1,2, 3 and 4 samples. In another example having proven to work well, thedecomposition unit is configured to generate the time-shifted componentsfrom the second sensor data in the form of PPG data by shifting it by−7, −5, −3, −1, 1, 3, 5 and 7 samples.

Combinations of the described different types of signal decomposition ofdifferent ones of these four groups of embodiments are possible andallow increasing the performance of the data processing device evenfurther. Such combinations comprise different stages of signaldecomposition in accordance with a selected combination of the differentembodiments. This may for instance be implemented by sequentiallyarranging two or more different stages of signal decomposition ofdifferent types in the decomposition unit.

In the following, different embodiments of the artifact removal unitwill be described.

Advantageously, the artifact removal unit is configured to determineindividual weights of the respective spectral and motion reference datachannels subject to the combination using a boundary condition, whichrequires that a weight vector that has as its vector components theindividual weights of the spectral channels and of the motion referencedata channels to be selected for the combination forms an optimum of acorrespondence measure indicative of a correspondence of the vitalsignal to a prestored normalized correlation vector.

A second aspect of the present embodiment is formed by an apparatus fordetermining a desired vital signal, which contains a physiologicalinformation component pertaining to a subject of interest, the apparatuscomprising:

-   -   an emitter unit, which comprises at least one emitter which is        configured to emit electromagnetic radiation in at least one        spectral channel that allows determining the physiological        information component;    -   a sensor unit, which is configured to ascertain and provide at        its output first sensor data that is indicative of an amount of        electromagnetic radiation reflected from or transmitted through        a sensed region of a subject of interest as a function of time        in at least one spectral channel that includes the physiological        information component and at least one motion artifact component        in a respective spectral region of the electromagnetic spectrum,        and to ascertain second sensor data that is indicative of a        position, a velocity or an acceleration of the sensed region as        a function of time in one or more spatial dimensions; and    -   a data processing device according to the first aspect of the        present embodiment or one of its embodiments described herein.

The apparatus of the second aspect of the embodiment shares theadvantages of the data processing device of the first aspect of theembodiment. The apparatus is advantageously based on thephotoplethysmography PPG technique.

Embodiments of the apparatus that are particularly suited for use inevery-day life and sports make use of PPG signals taken in differentspectral ranges. Such devices can be particularly compact. In suchembodiments, the emitter unit is additionally configured to emitelectromagnetic radiation in at least one second spectral channel thatis less sensitive to blood volume variations in the sensed region thanthe first spectral channel. The sensor unit is additionally configuredto ascertain PPG data indicative of an amount of electromagneticradiation reflected from or transmitted through the sensed region in theat least one second spectral channel.

Other embodiments provide, alternatively or additionally to theadditional spectral channel of PPG data, an accelerometer as a part ofthe sensor unit. Accelerometers based on semiconductor technology arewidely used in handheld device today and can be provided in very compactsize.

In a third aspect of the present embodiment, a data processing method isprovided method for extracting a desired vital signal, which contains aphysiological information component pertaining to a subject of interest,from sensor data, the data processing method comprising

-   -   receiving sensor data that includes time-dependent first sensor        data comprising the physiological information component and at        least one motion artifact component, and that includes        time-dependent second sensor data that is indicative of a        position, a velocity or an acceleration of the sensed region as        a function of time in one or more spatial dimensions, the:    -   decomposing the second sensor data into at least two components        of decomposed sensor data and providing, based on the decomposed        second sensor data, at least two different sets of motion        reference data in at least two different motion reference data        channels,    -   determining and providing as an output the vital signal formed        from a combination of the first sensor data and the motion        reference data of at least two of the motion reference data        channels.

The data processing method of the third aspect of the embodiment sharesthe advantages of the data processing device of the first aspect of theembodiment.

According to an embodiment of the embodiment, the method furthercomprises ascertaining sensor data that includes time-dependent firstsensor data comprising the physiological information component and atleast one motion artifact component, and that includes time-dependentsecond sensor data that is indicative of a position, a velocity or anacceleration of the sensed region as a function of time in one or morespatial dimension.

The operating method of the fourth aspect of the embodiment shares theadvantages of the data processing device of the first aspect of theembodiment.

In a fourth aspect of the embodiment, a computer program comprisingprogram code means for causing a computer to carry out the steps of thedata processing method of the third aspect of the embodiment or one ofits embodiments described herein, when said computer program is carriedout on a computer.

It shall be understood that the data processing device of the firstaspect of the embodiment, the PPG apparatus of the second aspect of theembodiment the data processing method of the third aspect of theembodiment, the operating method of the fourth aspect of the embodiment,and the computer program of the fifth aspect of the embodiment havesimilar and/or identical preferred embodiments.

BRIEF DESCRIPTION OF THE DRAWINGS

In the following drawings

FIG. 1 shows a block diagram of a first embodiment of a data processingdevice;

FIG. 2 shows a block diagram of a second embodiment of a data processingdevice;

FIG. 3 shows a block diagram of a first variant of a decomposition unitfor use in the first or second embodiment of the data processing device;

FIG. 4 shows a block diagram of a second variant of a decomposition unitfor use in embodiments of a data processing device according to thepresent embodiment;

FIG. 5 shows a block diagram of third variant of a decomposition unitfor use in embodiments of a data processing device according to thepresent embodiment;

FIG. 6 shows a block diagram of a fourth variant of a decomposition unitfor use in embodiments of a data processing device according to thepresent embodiment;

FIG. 7 shows a block diagram of an embodiment of an artifact removalunit for use in embodiments of a data processing device according to thepresent embodiment;

FIG. 8 shows a block diagram of a PPG apparatus according to anembodiment of the present embodiment;

FIG. 9 shows a flow diagram of an embodiment of a data processing methodaccording to the present embodiment; and

FIG. 10 shows a flow diagram of an embodiment for operating a PPGapparatus according to the present embodiment.

DETAILED DESCRIPTION OF EMBODIMENTS

Embodiments of the different aspects of the present embodiment describedin the following relate to an application in photoplethysmography. PPGhas been used widely over the past, for instance for an estimation ofcardiovascular parameters. This technique has been preferred over othertechniques such as a chest belt for electrocardiography (ECG) or anelectronic stethoscope because the latter two are often considered as areduction in comfort and usability. However, a motion of the subject ofinterest, i.e., the user or patient, during a PPG measurement generatesmotion artifacts in measured PPG signals. The artifacts lead toerroneous interpretation and degrade the accuracy and reliability ofestimation of cardiovascular parameters. The embodiments described inthe following achieve a particularly good reduction or full removal ofthese motion artifacts.

FIG. 1 shows a block diagram of a first embodiment of a data processingdevice 100. The data processing device serves for extracting a desiredvital signal, which contains a physiological information componentpertaining to a subject of interest, from first sensor data comprisingPPG data.

PPG data is data obtained by a PPG measurement before it is provided tothe data processing device. The PPG data may for instance be provided inthe form of sensor data generated by an optical sensor such as aphotodiode or a camera, and indicate a detected amount of light emittedby a light emitter (e.g., LED or laser diode) and reflected from or,depending on the measurement setup, transmitted through a sensed regionof a subject of interest as a function of time. The sensed region may bea region of the skin of the subject of interest. For instance the sensedregion may be region of skin of a finger or of an earlobe.

However, the present embodiment is concerned only with the processing ofthe provided PPG data in order to achieve motion artifact reduction orremoval.

The present exemplary embodiment of a data processing device 100 usesPPG data that is provided in the form of three different and separatestreams of data, which in FIG. 1 are labeled PPG1, PPG2, and PPG3. Thedifferent streams of PPG data represent PPG measurements taken inparallel (synchronously) in three spectral channels, that is, in threespectral intervals of the electromagnetic spectrum. More specifically, afirst PPG data stream PPG1, which is provided to the data processingdevice, comprises PPG data measured in a first spectral channel thatincludes the desired physiological information component and at leastone motion artifact component in a respective spectral region of theelectromagnetic spectrum. It is the purpose of the data processingdevice to extract the desired physiological information component,represented by what the present application calls the vital signal, fromthe measured PPG data. However, the vital signal is superimposed by themotion artifacts, and in some situations may even be hidden by motionartifacts present in the PPG data.

In particular, the spectral region covered by the first spectral channelincludes the wavelength region between 540 nm and 560 nm, which providesa particularly high sensitivity to blood volume variations. A suitablespectral region for the first spectral channel is for instance 530 to570 nm. However, a spectral channel narrower than this can also be used.The better the first spectral channel overlaps with the knowncharacteristic optical absorption and reflection features of blood inthe spectral region between 520 and 600 nm, the better is asignal-to-noise ratio of the PPG data PPG1 forming the first spectralchannel.

In the language of the claims, therefore, the first PPG data stream PPG1covering the first spectral channel provides first sensor data.

The PPG data assumed to be provided in the present embodiment furtherincludes two other data streams, a second PPG data stream PPG2 and athird PPG data stream PPG3, which represent PPG data measured in asecond and a third spectral channel. The second and third spectralchannels are selected to provide PPG data that is less sensitive toblood volume variations in the sensed region than the first spectralchannel. Suitable values are for example a spectral channel coveringwavelengths substantially around 650 nm, e.g., 610-700 nm. This spectralchannel provides a low pulsatility due to blood volume variations in theskin. Another suitable less sensitive spectral channel coverswavelengths substantially around 450 nm. Since the PPG data provided inthe second and third spectral channels is less sensitive to sensitivityto blood volume variations, the PPG data PPG2 and PPG3 includesrelatively less of the physiological information component andrelatively more at least one motion artifact component, which isindicative of a position, a velocity or an acceleration of the sensedregion as a function of time in one or more spatial dimensions.

In the language of the claims, therefore, the PPG data PPG2 in thesecond spectral channel and the PPG data PPG3 in the third spectralchannel form second sensor data.

The data processing device 100 receives the three different PPG datastreams PPG1 to PPG3 in an interface 102. The interface can beimplemented by any type of data interface suitable for receiving the PPGdata. It is noted that the PPG data need not be provided via threeseparate input ports of the interface 102. In variants, the PPG datacomprising the three different PPG data streams PPG1 to PPG3 is providedto a smaller number of input ports, for example in the form of a singledata stream that contains the three PPG data streams PPG1 to PPG3. Inthis case, the interface 102 is suitably configured to separate the PPGdata streams PPG1 to PPG3.

Downstream from the interface 102, a decomposition unit 104 receives thesecond sensor data only, i.e., the PPG data streams PPG2 and PPG3. Thedecomposition unit 104 comprises two parallel decomposition stages 104.1and 104.2. A first decomposition stage 104.1 receives the second PPGdata stream PPG2, and a second decomposition stage 104.2 receives thethird PPG data stream PPG3. The decomposition unit 104 is configured todecompose the second sensor data into at least two components ofdecomposed sensor data and to provide, based on the decomposed secondsensor data, at least two different sets of motion reference data in atleast two different motion reference data channels. The motion referencedata may be identical to the decomposed second sensor data.

In particular, in the present embodiment, motion reference data isprovided by the decomposition unit 104 in the form of a number of 2 mmotion reference data streams, wherein m is a positive integer. Each ofthe decomposition stages 104.1 and 104.2 provides a number of m motionreference data streams, which are labelled MR11, MR12, . . . , MR1 m forthose motion reference data streams provided by the first decompositionstage 104.1, and labelled MR21, MR22, . . . , MR2 m for those motionreference data streams provided by the second decomposition stage 104.2.The motion reference data streams contain similar motion artifacts asthe first PPG data stream PPG1, however, no a component due to bloodvolume variations (which may be called a heart-pulse component) or onlya weak component of this type. More details of the decomposition unit104.1 and the decomposition stages 104.2 and 104.3 will be explainedfurther below in the context of different embodiments described withreference to FIGS. 3 to 6.

The motion reference data streams are provided to an artifact removalunit 106. The artifact removal unit 106 also receives the first sensordata, that is, the three PPG data streams PPG1 to PPG3. The artifactremoval unit 106 is configured to determine and provide at its outputthe vital signal V formed from a combination, which in the presentnon-limiting example is a linear combination, of at least one of thespectral channels and at least one of the motion reference datachannels.

Motion artifacts often have harmonics that differ in energy. Thedecomposition of the second sensor data is used in the artifactreduction unit 106 to create more degrees of freedom where the artifactsare removed from the first sensor data, PPG1. Using more degrees offreedom tackles the problem of harmonics having different energies. Themotion artifact reduction can for instance be achieved by subtracting acombination, for example a linear combination of the generated motionreference data streams from the first PPG data stream PPG1.

The processing in the data processing device 100 is in particularembodiments done on a frame-by-frame basis. This provides the advantageof achieving motion artifact reduction or removal based on currentlyprocessed (frame) PPG data only, without having to refer to adaptationmechanisms for example that also require accessing previously processedPPG data.

The incoming PPG data are for instance first windowed into framesrepresenting segments of a number of seconds. In a variant of theembodiment of FIG. 1, thus, the interface unit additionally comprises aframing unit, which is configured to receive the incoming time-dependentPPG data and to partition it into frames representing segments of therespective PPG data covering a predetermined time interval, such as forexample a number of seconds.

A reconstruction of an incoming PPG data stream after the frameprocessing by the artifact removal unit can be achieved using anoverlap-add procedure. This is a well-known technique and will thereforenot be described here in more detail.

Details of the functionality and operation artifact removal unit 106will be described further below, in particular with reference to theembodiment of FIG. 7, after the description of different embodiments ofthe decomposition unit 104.

Variants of the embodiment of FIG. 1 receive PPG data cover only twospectral channels, such as for example provided by the PPG data streamsPPG1 and PPG2, or PPG1 and PPG3. In one such variant, the decompositionunit 104 may comprise only one decomposition stage. However, as will bedescribed further below in more detail, the number of decompositionstages need not be in strict correspondence to the number of data steamsreceived by the decomposition unit 104. In particular, the number ofdecomposition stage may be larger than the number of received datastreams, so as to provide a larger number of motion reference datastreams. Decomposition stages implementing different types ofdecomposition may be arranged sequentially and thus apply two differentforms of decomposition in sequence to an incoming data stream.

Another variant of the embodiment of FIG. 1 will be described in thefollowing with reference to FIG. 2. FIG. 2 shows a block diagram of asecond embodiment of a data processing device 200. The data processingdevice 200 corresponds to that of FIG. 1 in many aspects. In particular,it also contains an interface 202, a decomposition unit 204 and anartifact removal unit 206.

As in the embodiment of FIG. 1, the first sensor data comprises thefirst PPG data stream PPG1. In variants of the present embodiment, thedata streams PPG2 and PPG3 covering the second and third spectralchannels as described with reference to FIG. 1 are also provided asadditional components of the first sensor data, and therefore, like thefirst PPG data stream PPG1, are also directly routed from the interface202 to the artifact removal unit 206. These variants make use of thefact that the second and third data streams PPG2 and PPG3 typicallycontain at least some desired physiological information. Since thesedata streams PPG2 and PPG3 are optionally provided, the correspondingdata flow connections are indicated by dashed lines in FIG. 2.

In contrast to the embodiment of FIG. 1, data processing device 200receives the second sensor data in the form three different streams ofmotion data M1, M2, and M3, which are measured by techniques other thanPPG. Such motion data can for instance be determined using a sensor suchas an accelerometer, which provides data concerning a position, velocityand/or acceleration.

The decomposition unit 204 of the data processing device 200 comprisesthree decomposition stages 204.1 to 204.3, each which provides motionreference data based on one respective stream of incoming motion data. Afirst decomposition stage 204.1 uses the motion data M1 for providingdecomposed second sensor data in the form of m motion reference datastreams MR11, MR12, . . . , MR1 m. A second decomposition stage 204.2uses the motion data M2 for providing decomposed second sensor data inthe form of m motion reference data streams MR21, MR22, . . . , MR2 m. Athird decomposition stage 204.3 uses the motion data M3 for providingdecomposed second sensor data in the form of m motion reference datastreams MR31, MR32, . . . , MR3 m. Thus, a total number of 3 m motionreference data streams is output by the decomposition unit 204 andreceived by the artifact removal unit 206.

The data processing preformed by the data processing device 200 will bedescribed in more detail further below in the context of the followingembodiments.

The following description of the FIGS. 3 to 6 is concerned withdifferent variants of the decomposition stages 104.1, 104.2 or 204.1 to204.3 provided in the embodiments of FIGS. 1 and 2. These variants arenot meant as alternatives. On the opposite, they may be combined toadvantage. A decomposition unit may comprise a selection or cascade ofdecomposition stages and decomposition units of different type.Furthermore, use of the following variants is not restricted to thesetwo particular exemplary embodiments formed by the data processingdevices 100 and 200. Furthermore, examples of second sensor data usedthe following description are not meant as a limitation of any kind.

FIG. 3 shows a block diagram of a first variant of a decomposition stage300 for use in a decomposition unit of embodiments of the dataprocessing device. The decomposition unit 300 is configured to filterthe second sensor data as a function of time with respect to itsfrequency components, so as to provide the at least two components ofdecomposed second sensor data as a function of time in the form of tworespective frequency components the second sensor data. To this end thedecomposition unit 300 comprises a low-pass filter 302. As annon-restrictive example, the second sensor data is formed by the motiondata M1 mentioned in the context of FIG. 2. The low-pass filter 302receives the time-dependent motion data M1 and provides at its outputonly the low-frequency components of the motion data, while thehigh-frequency components are blocked by the low-pass filter 302.

For determining a suitable threshold frequency, the harmonics stemmingfrom movement should be taken into account. For instance, motionartifacts caused by jogging exhibit periodic components which lie around80 bpm (80/60 Hz) and have an octave component at 160 bpm (160/60 Hz). Asuitable threshold frequency in this case may be selected in the between80 and 160 bpm, such as for instance at 120 bpm (120/60 Hz).

The low-pass filtered motion data is provided as a first set of motionreference data MR11. A second set of motion reference data MR12 isprovided at the output of a difference stage 304, which receives at itsinputs the motion data M1 and the low-pass filtered motion data providedat the output of the low-pass filter 302 and provides as its output aquantity depending on the difference between the two inputs. This secondset of motion reference data MR12 is thus used to operate in the higherfrequency range. Thus, the motion data M1 is decomposed by thedecomposition stage 300 into two sets of motion reference data MR11 andMR12 in such a way that the data are ‘forced’ to operate in differentfrequency regions to reduce motion artifacts.

Without this decomposition the motion signals can reduce only thosemotion artifacts that are most prominent, e.g. the strongest harmonic,and are not able to reduce the other artifacts, e.g. the weakerharmonics. In exercises where there are strong periodic movements, e.g.jogging, the first and second harmonic of the motion artifacts areprominent and in the range of the heart-rate trace. Using this approachin combination with accelerometer signals reduces these two harmonicseffectively.

FIG. 4 shows a block diagram of a second variant of a decompositionstage 400 for use in a decomposition unit of embodiments of a dataprocessing device according to the present embodiment. A shift in phasemay occur across frequency between the first sensor data, i.e., one ormore channels of PPG sensor data, and motion data. This undesired effectyields a less optimal artifact reduction. To tackle this problem, aHilbert transform stage 402 is used. The Hilbert transform stage 402receives as input data the second sensor data, as is shown in FIG. 4 byway of example for the motion data M1. In a variant, one of thefrequency or phase components of the second sensor data (cf. theembodiment of FIG. 3) is provided as an input to the Hilbert transformstage 402. That is, in this variant the Hilbert transform stage 402 isarranged in sequence with the low-pass filter 302 or the differencestage 304.

The Hilbert transform stage is configured to provide at its outputHilbert transform data forming a Hilbert transform of the input data.This way, (additional) motion reference data is generated that isshifted in phase by −π/2 radians across frequency. The Hilberttransformed motion reference data MR12 and the original motion data M1as the other set MR12 of motion reference data are then fed to theartifact reduction unit, where it can be used to used to generate aphase-shifted version of a motion reference signal by θ radians. This isachieved by a combination, such as for instance a linear combination ofthe Hilbert transformed signal MR12 and its original signal M1. Thiswill be explained in further detail with reference to FIG. 7 below.

FIG. 5 shows a block diagram of third variant of a decomposition stage500 for use in a decomposition unit in embodiments of a data processingdevice according to the present embodiment. The decomposition stage 500comprises a singular spectrum analysis (SSA) unit, which is configuredto decompose the received second sensor data, such as the PPG data PPG2and PPG3 as a function of time using SSA into a sum of differentcomponents that form at least two components of the decomposed secondsensor data. SSA decomposes the received second sensor data into anumber of reconstructed components which include oscillatory components,varying trends and noise. The sum of these components results again inthe original signal. Depending on the eigenvalue spectra a number ofreconstructed components are chosen in combination with the originalsignal for artifact reduction.

The following steps are used to compute the reconstructed componentsfrom a mean corrected segment of a motion reference signal, say s(n)with n∈{1, . . . , N}. Based on an embedded dimension K and thedefinition L:=N+1−K, a L×K Hankel matrix S=[s₀, s₁, . . . , s_(K)] isformed in a Hankel forming unit 502. Here, s_(k) are column vectors withelements s_(k):=[s(k), s(k+1), . . . , s(k+L−1)]^(T). Based on thedetermined Hankel matrix S, an eigenvalue determination unit 504determines eigenvalues λ₁≥λ≥ . . . ≥λ_(K)≥0 and eigenvectors v₁, . . . ,v_(K) of the covariance matrix S^(T)S. A projection unit 506 projects Sonto the eigenvectors A:=SV, where A is a matrix containing theprincipal components a_(k) as columns and V a matrix with eigenvectorsv_(k) as columns. The reconstructed components r_(k)(n) are determinedin a component reconstruction unit 508 by determining

${{r_{k}(n)}:={\frac{1}{M_{n}}{\sum\limits_{m = L_{n}}^{U_{n}}{{a_{k}\left( {n - m + l} \right)}{v_{K}(m)}}}}},$with (M_(n),L_(n),U_(n))=(1/n,1,n) for 1≥n≥M−1,(M_(n),L_(n),U_(n))=(1/M,1,M) for M≥n≥K and(M_(n),L_(n),U_(n))=(1/(N−n+1),n−N+M,M) for K+1≥n≥N.

Experiments show that the present SSA embodiment works well for instancefor N=128 at a sample rate of 16 Hz, and K=24. It is noted that a windowlength of 24 samples encompasses at least one complete period of a heartpulse.

FIG. 6 shows a block diagram of a fourth variant of a decomposition unit600 for use in embodiments of a data processing device according to thepresent embodiment. In the decomposition unit 600, the second sensordata, such as in the present example the second PPG data stream PPG2, isdecomposed into m sets of motion reference data MR11, MR12, MR13, . . ., MR1 m by shifting the PPG data samples by different amounts k ofsamples, k∈Z. To this end, m shifting stages are provided, from whichthe first three shifting stage 602, 604, 606 and the last shifting stage608 are shown in FIG. 6. For example, a decomposition into eight signalsis realized by shifting the PPG data stream PPG2 by −4, −3, −2, −1, 1,2, 3 and 4 samples. An embodiment tested in experiments shows thatartifact reduction works well by shifting PPG data by −7, −5, −3, −1, 0,1, 3, 5 and 7 samples. The zero-shift component may be obtained directlyfrom the second PPG data stream PPG2 and thus need not be passed througha shifting stage.

In the following, further embodiments will be explained that differ intheir respective artifact removal unit. Reference is made to FIG. 7,which shows a block diagram of an embodiment of an artifact removal unitfor use in embodiments of a data processing device according to thepresent embodiment. For the purpose of the description to follow, thedesired artifact reduced PPG signal is denoted as s(t), and a sampledsignal, i.e., a desired set of artifact reduced PPG data, is denoted ass(k).

In a first embodiment of the artifact removal unit 700, weights w_(i)are computed by a weight determination stage 702 for the received firstsensor data and the motion reference data such that the artifact reducedsampled PPG data is constructed in a vital signal construction stage 704as follows:s(k)=W ₀ x ₀(k)+W ₁ x ₁(k)+ . . . +W _(L) x _(L)(k)

Here, L=N·M, x₀(k) is the first sensor data PPG1, and x₁(k), . . . ,x_(K)(k) are the are the motion reference data provided by thedecomposition unit. The weights W_(i) are computed solving a system oflinear equationsX ^(T) Xw=b,

where X=[x₀, x₁, . . . , x_(L)] is a K×L matrix with x_(i)=[x_(i)(1),x_(i)(2), . . . , x_(i)(K)]^(T). The vector w contains the weightsW_(i), and the elements of the prestored normalized correlation vectorb, which is stored in a memory 706, represent the a priory predictednormalized correlations among the vectors x_(i).

In one variant, b=[1, 0 . . . , 0] for zero correlation is predictedbetween the vital sign and the motion reference signals.

A second embodiment of the artifact removal unit 700, which has the samegeneral structure as the previous embodiment and will therefore bedescribed with continued reference to FIG. 7, is based on the embodimentof FIG. 2. Additional PPG data PPG2 of a longer wavelength, e.g. 650 nm,is fed into the artifact reduction module in this variant. This dataPPG2 is closely related to PPG1 containing similar motion artifacts, buthas a lower pulsatility. As in the first embodiment of FIG. 7 weightsare computed by solving a system of linear equations. The a prioripredicted normalized correlation vector is b=[C, aC, 0, . . . , 0],∥b∥=1, where C provides the normalized correlation between the desiredvital signal and PPG1, and aC, a<1 provides the correlation between thedesired vital signal and PPG2. In this case x₀(t) and x₁(t) are thefirst sensor data comprising the PPG data PPG1 and PPG2 and x_(l)(t),l∈{2, . . . , L+1} the motion reference data. Experiments have shownthat a value of a=0.1 works well for motion artifact reduction. Theparameter C is used to normalize the vector b and is computed from agiven value of a and a given norm. In the exemplary case of a=0.1 andthe L2 norm, C=1/√{square root over (l²+0.1²)}.

A third embodiment of the artifact removal unit 700, which has the samegeneral structure as the previous embodiment and will therefore bedescribed with continued reference to FIG. 7, and is also based on theembodiment of FIG. 2. Further Additional PPG data PPG3 of a shorterwavelength, e.g. 450 nm, is fed into the artifact reduction module inthis variant in addition to the PPG data PPG1 and PPG2. As in first andsecond embodiments a prestored a priory correlation vector is used,extended with a correlation between the vital sign and PPG3: b=[C, aC,bC, . . . , 0], ∥b∥=1, with 1>b>a. In this case, x₀(t), x₁(t), and x₂(t)correspond to the first sensor data, and are formed by the PPG dataPPG1, PPG2, and PPG3, respectively. The motion reference data isx_(l)(t), l∈{3, . . . , L+2}. Experiments have shown that a value ofa=0.1 and b=0.5 works well for motion artifact reduction.

Further sets of PPG data representing more than three different spectralchannels may be used in other variants. As in the embodiments describedan a priory correlation vector is composed extended with correlationsbetween the vital signal and the (decomposed) sets of PPG signals

In a fourth embodiment of the artifact removal unit 700, which forms avariant of the first embodiment, has the same general structure and willthus also be described with continued reference to FIG. 7, thedimensionality of the matrix X^(T)X is reduced by one in comparison withthe first embodiment of the artifact removal unit 700. In thisembodiment, the normalized correlation vector is b=[1, 0, . . . , 0].For this case the problem can be formulated as follows:X ^(T) Xw=b,

with X=[x₁, . . . , x_(L)] and b=X^(T)x₀. The artifact reduced PPG datais thens(k)=x ₀(k)−(w ₁ x ₁(k)+ . . . +w _(L) x _(L)(k)).

In a fifth embodiment of the artifact removal unit, which is used in anembodiment of a data processing device comprising decomposition unit500, the same general structure of the artifact removal unit 700 of FIG.7 can be used. Experiments show that suitable prestored correlationvector [C, a₁C, a₂C, . . . a_(n)C] has the components a₁=c, a₂=c·α₁, . .. a_(n)=c·α_(n+1) with α_(i)=λ_(i)/λ₁, wherein λ_(i) are the eigenvaluescomputed from the SSA method. For the case n=5 a value of c≈1/20 can beused to achieve good motion artifact reduction.

In a sixth embodiment of the artifact removal unit, which is used in anembodiment of the data processing device that has a decomposition unitusing decomposition stages of the type shown in FIG. 6, the normalizedcorrelation vector [C, a₁C, a₂C, . . . a_(n)C] can be chosen as follows:a_(i)=c·cos(k_(i)φ), where k_(i)∈

, i∈{1, . . . , n} is a number equivalent to the sample shift in x_(i),and a phase φ=2πF/f, where F is a default pulse rate in Hz and f thesample rate in Hz. Experiments have shown that this method works wellwith c≈1/20, F=2, and k_(i)=[0,1,−1,3,−3,5,−5,7,−7]. A furtherimprovement could be possible by predicting F from the current frameinstead of using a default value for the expected pulse-rate F. Asuitable parameter for predicting F is for instance indicative of amotion rate estimated from the current frame.

FIG. 8 shows a block diagram of a PPG apparatus 800 according to anembodiment of the present embodiment. The for PPG apparatus serves fordetermining a desired vital signal, which contains a physiologicalinformation component pertaining to a subject of interest. The PPGapparatus 800 comprises an emitter unit 802, which comprises at leastone emitter which is configured to emit electromagnetic radiation in atleast one spectral channel that allows determining the physiologicalinformation component. In the PPG apparatus 800, three different lightemitters operating in different spectral channels are indicated byarrows 802.1, 802.2, 803.3.

A sensor unit 804, using for example three sensors 804.1, 804.2, 804.3is configured to ascertain and provide at its output first sensor dataPPG1 that is indicative of an amount of electromagnetic radiationreflected from or transmitted through a sensed region of a subject ofinterest as a function of time in at least one spectral channel thatincludes the physiological information component and at least one motionartifact component in a respective spectral region of theelectromagnetic spectrum, and to ascertain second sensor data PPG2, PPG3that is indicative of a position, a velocity or an acceleration of thesensed region as a function of time in one or more spatial dimensions.The PPG apparatus further comprises a data processing device 806 inaccordance with one of the embodiments of the data processing devicedescribed herein, for instance with reference to the FIGS. 1 to 7 above.

FIG. 9 shows a flow diagram of an embodiment of a data processing method900 according to the present embodiment. The data processing method 900serves for extracting a desired vital signal, which contains aphysiological information component pertaining to a subject of interest,from sensor data.

In a step 902 sensor data is received that includes time-dependent firstsensor data comprising the physiological information component and atleast one motion artifact component. The sensor data also includestime-dependent second sensor data that is indicative of a position, avelocity or an acceleration of the sensed region as a function of timein one or more spatial dimensions.

In a step 904, the second sensor data is decomposed into at least twocomponents of decomposed sensor data. Based on the decomposed secondsensor data, at least two different sets of motion reference data isprovided in at least two different motion reference data channels.

In a step 906, the vital signal formed from a linear combination of thefirst sensor data and the motion reference data of at least one two ofthe motion reference data channels it is determined and provided as anoutput.

FIG. 10 shows a flow diagram of an embodiment for operating a PPGapparatus according to the present embodiment. The method comprisesascertaining sensor data in a step 1002. As described before, the sensordata includes time-dependent first sensor data comprising thephysiological information component and at least one motion artifactcomponent, and it includes time-dependent second sensor data that isindicative of a position, a velocity or an acceleration of the sensedregion as a function of time in one or more spatial dimension. In a step1004, the data processing method 900 is performed.

While the embodiment has been illustrated and described in detail in thedrawings and foregoing description, such illustration and descriptionare to be considered illustrative or exemplary and not restrictive; theembodiment is not limited to the disclosed embodiments. Other variationsto the disclosed embodiments can be understood and effected by thoseskilled in the art in practicing the claimed embodiment, from a study ofthe drawings, the disclosure, and the appended claims.

In the claims, the word “comprising” does not exclude other elements orsteps, and the indefinite article “a” or “an” does not exclude aplurality.

A single stage or other unit may fulfill the functions of several itemsrecited in the claims. The mere fact that certain measures are recitedin mutually different dependent claims does not indicate that acombination of these measured cannot be used to advantage.

A computer program may be stored/distributed on a suitable medium, suchas an optical storage medium or a solid-state medium supplied togetherwith or as part of other hardware, but may also be distributed in otherforms, such as via the Internet or other wired or wirelesstelecommunication systems.

Any reference signs in the claims should not be construed as limitingthe scope.

The invention claimed is:
 1. A data processing device for using improvedmotion artifact reduction to extract a desired vital signal, whichcontains a physiological information component pertaining to a subjectof interest, from sensor data that includes time-dependent first sensordata, obtained from a sensed region in a first spectral channel that issensitive to blood volume variations, and comprising the physiologicalinformation component and at least one motion artifact component, andthat includes time-dependent second sensor data in the form ofphotoplethysmography data, obtained simultaneously with the first sensordata, wherein the photoplethysmography data is indicative of a position,a velocity or an acceleration of the sensed region as a function of timein one or more spatial dimensions; the data processing devicecomprising: a decomposition unit, which is configured to receive thesecond sensor data, to decompose the second sensor data into at leasttwo components of decomposed second sensor data and to provide, based onthe decomposed second sensor data, at least two different sets of motionreference data in at least two different motion reference data channels,wherein the decomposition unit is configured to filter the second sensordata as a function of time with respect to its phase components, so asto provide the at least two components of decomposed second sensor dataas a function of time in the form of at least two respective phasecomponents of the second sensor data that are phase shifted relative toeach other, and an artifact removal unit, which is configured to receivethe first sensor data and the at least two different motion referencedata channels, and to determine and provide at its output the vitalsignal (V) formed from a combination of the first sensor data and themotion reference data of at least two of the motion reference datachannels; and wherein the photoplethysmography data is indicative of anamount of electromagnetic radiation reflected from or transmittedthrough the sensed region in at least one second spectral channel thatis less sensitive to blood volume variations in the sensed region thanthe first spectral channel.
 2. The data processing device of claim 1,wherein the artifact removal unit is configured to determine individualweights of the respective spectral and motion reference data channelssubject to the combination using a boundary condition, which requiresthat a weight vector that has as its vector components the individualweights of the spectral channels and of the motion reference datachannels to be selected for the combination forms an optimum of acorrespondence measure indicative of a correspondence of the vitalsignal to a prestored normalized correlation vector (b).
 3. The dataprocessing device of claim 1, which is configured to structure thetime-dependent first and second sensor data into frames containingsensor data pertaining to predetermined time spans, wherein thedecomposition unit is configured to decompose the second sensor data ona frame-by-frame basis, and the artifact removal unit is configured todetermine the combination of the first sensor data and the motionreference data on the frame-by-frame basis.
 4. The data processingdevice of claim 1, wherein the at least two respective phase componentsof the second sensor data are phase shifted by −π/2 radians relative toeach other.
 5. An apparatus for using improved motion artifact reductionto determine a desired vital signal, which contains a physiologicalinformation component pertaining to a subject of interest, the apparatuscomprising: an emitter unit, which comprises at least one emitter whichis configured to emit electromagnetic radiation in at least a firstspectral channel that allows determining the physiological informationcomponent; a sensor unit, which is configured to: ascertain and provideat its output first sensor data that is indicative of an amount ofelectromagnetic radiation reflected from or transmitted through a sensedregion of a subject of interest as a function of time in the firstspectral channel that includes the physiological information componentand at least one motion artifact component in a respective spectralregion of the electromagnetic spectrum, and ascertain second sensor datain the form of photoplethysmography data that is indicative of aposition, a velocity or an acceleration of the sensed region as afunction of time in one or more spatial dimensions, wherein thephotoplethysmography data is indicative of an amount of electromagneticradiation reflected from or transmitted through the sensed region in atleast one second spectral channel that is less sensitive to blood volumevariations in the sensed region than the first spectral channel; adecomposition unit that is configured to receive the second sensor data,to decompose the second sensor data into at least two components ofdecomposed second sensor data and to provide, based on the decomposedsecond sensor data, at least two different sets of motion reference datain at least two different motion reference data channels, is configuredto filter the second sensor data as a function of time with respect toits phase components, so as to provide the at least two components ofdecomposed second sensor data as a function of time in the form of atleast two respective phase components of the second sensor data that arephase shifted relative to each other; and an artifact removal unit,which is configured to receive the first sensor data and the at leasttwo different motion reference data channels, and to determine andprovide at its output the desired vital signal formed from a combinationof the first sensor data and the motion reference data of at least twoof the motion reference data channels.
 6. The apparatus of claim 5,wherein the emitter unit is additionally configured to emitelectromagnetic radiation in the at least one second spectral channelthat is less sensitive to blood volume variations in the sensed regionthan the first spectral channel, the sensor unit is configured toascertain data indicative of an amount of electromagnetic radiationreflected from or transmitted through the sensed region in the at leastone second spectral channel.
 7. The apparatus of claim 5, wherein the atleast two respective phase components of the second sensor data arephase shifted by −π/2 radians relative to each other.
 8. A dataprocessing method for using improved motion artifact reduction toextract a desired vital signal, which contains a physiologicalinformation component pertaining to a subject of interest, from sensordata, the data processing method comprising: receiving sensor data inthe form of photoplethysmography data that includes time-dependent firstsensor data, obtained from a sensed region in a first spectral channel,comprising the physiological information component and at least onemotion artifact component, and that includes time-dependent secondsensor data in the form of photoplethysmography data, obtainedsimultaneously with the first sensor data, wherein thephotoplethysmography data is indicative of a position, a velocity or anacceleration of the sensed region as a function of time in one or morespatial dimensions, decomposing the second sensor data into at least twocomponents of decomposed second sensor data and providing, based on thedecomposed second sensor data, at least two different sets of motionreference data in at least two different motion reference data channels,wherein the decomposing includes filtering the second sensor data as afunction of time with respect to its phase components, so as to providethe at least two components of decomposed second sensor data as afunction of time in the form of at least two respective phase componentsof the second sensor data that are phase shifted relative to each other,and determining and providing as an output the vital signal formed froma combination of the first sensor data and the motion reference data ofat least two of the motion reference data channels; wherein thephotoplethysmography data is indicative of an amount of electromagneticradiation reflected from or transmitted through the sensed region in atleast one second spectral channel that is less sensitive to blood volumevariations in the sensed region than the first spectral channel.
 9. Anon-transitory computer readable medium, said medium comprising acomputer program comprising program code means for causing a computer tocarry ou the steps of the method as claimed in claim 8 when saidcomputer program is carried out on a computer.
 10. The data processingmethod of claim 8, wherein the at least two respective phase componentsof the second sensor data are phase shifted by −π/2 radians relative toeach other.